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Hybrid genetic algorithms with selective crossover for the capacitated p-median problem

Author

Listed:
  • L’udmila Jánošíková

    (University of Žilina)

  • Miloš Herda

    (University of Žilina)

  • Michal Haviar

    (University of Žilina)

Abstract

The paper suggests two ways of combining a genetic algorithm with integer programming to improve the quality of the problem solution. The motivation is that today’s integer programming solvers are very sophisticated and efficient, and they are worth utilizing in combination with metaheuristics to solve hard combinatorial optimization problems. The capacitated p-median problem is chosen as an example of a problem that is intractable for an exact method and that needs a heuristic or metaheuristic method, e.g. a genetic algorithm, to get a near-optimal solution. A genetic algorithm can be combined with integer programming in such a way that the metaheuristic acts at a higher level and controls the calls to the solver, or the solver can be used as a post-processing technique to improve the best solution. Two variants of the hybrid genetic algorithm are tested using benchmark instances. Moreover, a new crossover operator is proposed, that uses the knowledge of the problem domain to preserve only positive traits of the parents in the offspring. The computational experiments suggest that the operator enables to improve the behaviour of the genetic algorithm.

Suggested Citation

  • L’udmila Jánošíková & Miloš Herda & Michal Haviar, 2017. "Hybrid genetic algorithms with selective crossover for the capacitated p-median problem," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(3), pages 651-664, September.
  • Handle: RePEc:spr:cejnor:v:25:y:2017:i:3:d:10.1007_s10100-017-0471-1
    DOI: 10.1007/s10100-017-0471-1
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    References listed on IDEAS

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    2. Felder, Stefan & Brinkmann, Henrik, 2002. "Spatial allocation of emergency medical services: minimising the death rate or providing equal access?," Regional Science and Urban Economics, Elsevier, vol. 32(1), pages 27-45, January.
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    Cited by:

    1. Snežana Tadić & Mladen Krstić & Željko Stević & Miloš Veljović, 2023. "Locating Collection and Delivery Points Using the p -Median Location Problem," Logistics, MDPI, vol. 7(1), pages 1-17, February.
    2. Janez Povh & Lidija Zadnik Stirn & Janez Žerovnik, 2017. "Editorial," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 25(3), pages 521-523, September.
    3. Andrej Kastrin & Janez Povh & Lidija Zadnik Stirn & Janez Žerovnik, 2021. "Methodologies and applications for resilient global development from the aspect of SDI-SOR special issues of CJOR," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 29(3), pages 773-790, September.
    4. Mai, Feng & Fry, Michael J. & Ohlmann, Jeffrey W., 2018. "Model-based capacitated clustering with posterior regularization," European Journal of Operational Research, Elsevier, vol. 271(2), pages 594-605.
    5. A. D. López-Sánchez & J. Sánchez-Oro & M. Laguna, 2021. "A New Scatter Search Design for Multiobjective Combinatorial Optimization with an Application to Facility Location," INFORMS Journal on Computing, INFORMS, vol. 33(2), pages 629-642, May.

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